Revisorers användning av artificiellintelligens : En kvantitativ studie om hur utbildning, upplevd AI-kompetens och tillit till AI påverkar AI-användning

Sammanfattning

Auditors’ Use of Artificial Intelligence A Quantitative Study of How Training, Perceived AI Competence and Trust in AI Influence AI Use Our conceptual model, which is based on the basic Technology Acceptance Model (TAM), supplemented with Perceived Self-Ability, Trust in Automated Systems and Human Capital Theory, aims to analyze the relationships between AI training, perceived AI competence, trust in AI and self-reported use of AI in audit work. The study is based on a quantitative survey aimed at authorized public accountants in Sweden. The data material includes 92 responses and was analyzed with descriptive statistics, reliability analysis, regression analysis and mediation analysis. The results show that both AI training and training on AI's limitations have positive and significant relationships with perceived AI competence. Perceived AI competence in turn has a positive and significant relationship with the use of AI. Trust in AI also has a positive and significant relationship with the use of AI. When all main variables are analyzed together, perceived AI competence and trust in AI are the variables that have significant relationships with the use of AI in audit work. The mediation analysis shows that AI training has an indirect relationship with AI use through perceived AI competence. The study contributes to the research on AI adoption in auditing by shifting the focus from technology and organization to the auditor as an individual user. By showing how training, perceived AI competence, trust and use are related, the study contributes to a more nuanced understanding of AI use in auditing work. The results indicate that training is primarily related to AI use by strengthening the auditor's perceived AI competence, while trust in AI is an important complementary factor.